Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition).
Define workflows where each step in the workflow is a container.
Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG).
Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes.
Run CI/CD pipelines natively on Kubernetes without configuring complex software development products.
Workflow templating to store commonly used Workflows in the cluster
Archiving Workflows after executing for later access
Scheduled workflows
Server interface with REST API
DAG or Steps based declaration of workflows
Step level input & outputs (artifacts/parameters)
Loops
Parameterization
Conditionals
Timeouts (step & workflow level)
Retry (step & workflow level)
Resubmit (memoized)
Suspend & Resume
Cancellation
K8s resource orchestration
Exit Hooks (notifications, cleanup)
Garbage collection of completed workflow
Scheduling (affinity/tolerations/node selectors)
Volumes (ephemeral/existing)
Parallelism limits
Daemoned steps
DinD (docker-in-docker)
Script steps
Event emission
Prometheus metrics
Multiple executors
Multiple pod and workflow garbage collection strategies
Automatically calculated resource usage per step
Pod Disruption Budget support
Community Meetings
We host monthly community meetings where we and the community showcase demos and discuss the current and future state of the project. Feel free to join us! For Community Meeting information, minutes and recordings please see here.